Method and Computer for Indexing and Searching Structures

ABSTRACT

A method for indexing a plurality of structures, which are derived from a plurality of externalizations of users&#39; mental models, is provided. The method comprises receiving at least one of the plurality of structures; analyzing the at least one structure according to a predetermined principle of normalization to obtain a plurality of index analysis results in a form of a plurality of tuples comprising a plurality of elements and/or a plurality of relations thereof related to the plurality of structures; and generating an index store according to the index analysis result; wherein each externalized relation indicates each externalized sequence from one of externalized elements to another one of the externalized elements; wherein each relation indicates each sequence from one of a plurality of elements to another one of the plurality of elements.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation application of U.S. application Ser. No.14/027,151, filed Sep. 13, 2013 and claiming the benefit of both U.S.Provisional Application No. 61/702,268, filed on Sep. 18, 2012 andentitled “METHODS AND SYSTEMS FOR STRUCTURAL INDEX AND SEARCH WITH OPENSCHEMA” and U.S. Provisional Application No. 61/708,634, filed on Oct.1, 2012 and entitled “SEARCH SYSTEMS AND METHODS GROUNDED ON STRUCTURALCOGNITIVE CHARACTERISTICS”, which is included in its entirety herein byreference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The application relates to a method and a computer system for indexingand searching a plurality of structures, and more particularly, to amethod and a computer system for indexing and searching a plurality ofstructures derived from a plurality of externalizations of users' mentalmodels.

2. Description of the Prior Art

To address the issue of retrieving documents from certain corpuses,conventional search engines take the following approach: extractingmeaningful words from documents and taking them as units for indexing,building inverted index files accordingly, calculating degrees ofrelevance between user specified queries and all indexed documentswhenever a user query comes in, and returning documents with higherdegree of relevance to the user.

Conventional search engines ask users to provide one or more keywords tospecify their documents of interests. However, without structuralimplications, search service systems often return documents containinguser-specified query terms but hardly meeting users' demands asexpected. The reason is that users' interests or intentions could not beprecisely identified by only a number of separate tokens. In essence,the presentation of a user's intent is to be defined in terms of her/hisown interpretation or recognition associated with the query targets.Users interpret and locate their search targets, as an object incognition, within an established mental schema or cognition, andinterpret their understandings of the search targets with pre-conceivedideas in particular schema (s). Such schema revealed in cognition arehierarchical or inter-related, in other words, are structural; andmultiple tags that do not bear structural implications cannot representhierarchies and inter-relationships existing in different concepts incognition. However, popular modern search engines request informationseekers to use multiple keywords without structural implications tospecify their query targets, and result in inefficient searching for theinformation seekers.

Moreover, individuals' ontologies or categorizations for externallymodel a knowledge domain might be different due to diverse backgroundknowledge and different interpretations. Each one may specify the querytargets based on her/his individual ontologies or categorizations, whichcontributes lots of improvements for the search service systems toprovide precise responses corresponding to different users'requirements. Therefore, it is an important issue to provide aninnovative approach for indexing and searching the plurality ofstructures that are derived from the externalization of users' mentalmodels.

SUMMARY OF THE INVENTION

It is therefore an objective of the invention to provide a method and acomputer system for indexing and searching a plurality of structuresderived from a plurality of externalizations of users' mental models.

An embodiment of the invention discloses a method for indexing aplurality of structures, which are derived from a plurality ofexternalizations of users' mental models, the method comprisingreceiving at least one of the plurality of structures; analyzing the atleast one structure according to a predetermined principle ofnormalization to obtain a plurality of index analysis results in a formof a plurality of tuples comprising a plurality of elements and/or aplurality of relations thereof related to the plurality of structures;and generating an index store according to the index analysis result;wherein the plurality of externalizations of users' mental models areobtained via a mind map, a concept map, a knowledge map, a diagram, aflow, a chart or a category; wherein each of the plurality ofexternalizations of users' mental models is an established mental schemaor cognition for interpreting users' understandings of certain searchtargets in a form of externalized elements and externalized relationsthereof, and each of the externalized relations indicates eachexternalized sequence from one of the externalized elements to anotherone of the externalized elements; wherein each of the plurality ofstructures derived from a corresponding one of the plurality ofexternalizations of users' mental models comprises a plurality ofelements and a plurality of relations thereof, each of the plurality ofelements is obtained via a text, an image, a sound, a video or anysymbols representing a user's concept, conception, idea or other mentalcontents, and each of the plurality of relations is obtained as ahierarchy, a sequential order, a logical dependency or other specifiedstates of affairs among the plurality of elements and indicates eachsequence from one of the plurality of elements to another one of theplurality of elements.

Another embodiment of the invention also discloses a computer system forindexing a plurality of structures, which are derived from a pluralityof externalizations of users' mental models, the computer systemcomprising a central processing unit; a user interface coupled to thecentral processing unit; and a storage device coupled to the centralprocessing unit for storing a programming code, and the programming codeis utilized to instruct the central processing unit for processing amethod comprising receiving at least one of the plurality of structuresvia the user interface; analyzing the at least one structure accordingto a predetermined principle of normalization to obtain a plurality ofindex analysis results in a form of a plurality of tuples comprising aplurality of elements and/or a plurality of relations thereof related tothe plurality of structures; and generating an index store according tothe index analysis result; wherein the plurality of externalizations ofusers' mental models are obtained via a mind map, a concept map, aknowledge map, a diagram, a flow, a chart or a category; wherein each ofthe plurality of externalizations of users' mental models is anestablished mental schema or cognition for interpreting users'understandings of certain search targets in a form of externalizedelements and externalized relations thereof, and each of theexternalized relations indicates each externalized sequence from one ofthe externalized elements to another one of the externalized elements;wherein each of the plurality of structures derived from a correspondingone of the plurality of externalizations of users' mental modelscomprises a plurality of elements and a plurality of relations thereof,each of the plurality of elements is obtained via a text, an image, asound, a video or any symbols representing a user's concept, conception,idea or other mental contents, and each of the plurality of relations isobtained as a hierarchy, a sequential order, a logical dependency orother specified states of affairs among the plurality of elements andindicates each sequence from one of the plurality of elements to anotherone of the plurality of elements.

Another embodiment of the invention also discloses a method forsearching a plurality of structures, which are derived from a pluralityof externalizations of users' mental models, the method comprisingreceiving at least one search query identifying one of the plurality ofstructures; analyzing the at least one structure according to apredetermined principle of normalization, to obtain a plurality ofsearch analysis results in a form of a plurality of tuples comprising aplurality of elements and/or a plurality of relations thereof related tothe plurality of structures; processing an identification search processto identify, in an index store, a plurality of structures comprising atleast one of the plurality of tuples; performing a calculation operationfor a plurality of identified structures according to predeterminedprinciples of relevancy, so as to obtain a plurality of relevancyanalysis results; ranking the plurality of identified structuresaccording to the plurality of relevancy analysis results, to obtain asearch report; and outputting the search report to a user's terminal;wherein the predetermined principles of relevancy comprise at least oneor more principles of similarity calculation for the plurality ofstructures, and the plurality of externalizations of users' mentalmodels are obtained via a mind map, a concept map, a knowledge map, adiagram, a flow, a chart, or a category; wherein each of the pluralityof externalizations of users' mental models is an established mentalschema or cognition for interpreting users' understandings of certainsearch targets in a form of externalized elements and externalizedrelations thereof, and each of the externalized relations indicates eachexternalized sequence from one of the externalized elements to anotherone of the externalized elements; wherein each of the plurality ofstructures derived from a corresponding one of the plurality ofexternalizations of users' mental models comprises a plurality ofelements and a plurality of relations thereof, each of the plurality ofelements is obtained via a text, an image, a sound, a video or anysymbols representing a user's concept, conception, idea or other mentalcontents, and each of the plurality of relations is obtained as ahierarchy, a sequential order, a logical dependency or other specifiedstates of affairs among the plurality of elements and indicates eachsequence from one of the plurality of elements to another one of theplurality of elements.

Another embodiment of the invention also discloses a computer system forsearching a plurality of structures, which are derived from a pluralityof externalizations of users' mental models, the computer systemcomprising a central processing unit; a user interface coupled to thecentral processing unit; and a storage device coupled to the centralprocessing unit for storing a programming code, and the programming codeis utilized to instruct the central processing unit for processing amethod comprising receiving at least one search query identifying one ofthe plurality of structures via the user interface; analyzing the atleast one structure according to a predetermined principle ofnormalization, to obtain a plurality of search analysis results in aform of a plurality of tuples comprising a plurality of elements and/ora plurality of relations thereof related to the plurality of structures;processing an identification search process to identify, in an indexstore, a plurality of structures comprising at least one of theplurality of tuples; performing a calculation operation for a pluralityof identified structures according to predetermined principles ofrelevancy, so as to obtain a plurality of relevancy analysis results;ranking the plurality of identified structures according to theplurality of relevancy analysis results, to obtain a search report; andoutputting the search report to a user's terminal via the userinterface; wherein the predetermined principles of relevancy comprise atleast one or more principles of similarity calculation for the pluralityof structures, and the plurality of externalizations of users' mentalmodels are obtained via a mind map, a concept map, a knowledge map, adiagram, a flow, a chart, or a category; wherein each of the pluralityof externalizations of users' mental models is an established mentalschema or cognition for interpreting users' understandings of certainsearch targets in a form of externalized elements and externalizedrelations thereof, and each of the externalized relations indicates eachexternalized sequence from one of the externalized elements to anotherone of the externalized elements; wherein each of the plurality ofstructures derived from a corresponding one of the plurality ofexternalizations of users' mental models comprises a plurality ofelements and a plurality of relations thereof, each of the plurality ofelements is obtained via a text, an image, a sound, a video or anysymbols representing a user's concept, conception, idea or other mentalcontents, and each of the plurality of relations is obtained as ahierarchy, a sequential order, a logical dependency or other specifiedstates of affairs among the plurality of elements and indicates eachsequence from one of the plurality of elements to another one of theplurality of elements.

These and other objectives of the present invention will no doubt becomeobvious to those of ordinary skill in the art after reading thefollowing detailed description of the preferred embodiment that isillustrated in the various figures and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic diagram of a computer system according toan embodiment of the invention.

FIG. 2 is a flow chart of an index process according to an embodiment ofthe invention.

FIG. 3 is a flow chart of a search process according to an embodiment ofthe invention.

FIG. 4 illustrates a schematic diagram of a general categorizationaccording to an embodiment of the invention.

FIG. 5 illustrates a schematic diagram of a mind map according to anembodiment of the invention.

FIG. 6 illustrates a schematic diagram of an index schematic tableaccording to an embodiment of the invention.

FIG. 7 illustrates another schematic diagram of an index schematic tableaccording to an embodiment of the invention.

FIG. 8 illustrates a schematic diagram of another index schematic tablewith ranking according to an embodiment of the invention.

DETAILED DESCRIPTION

The specification and the claims of the present invention may use aparticular word to indicate an element, which may have diversified namesnamed by distinct manufacturers. The present invention distinguishes theelement depending on its function rather than its name. The phrase“comprising” used in the specification and the claim is to mean “isinclusive or open-ended but not exclude additional, un-recited elementsor method steps.” In addition, the phrase “electrically connected to” or“coupled” is to mean any electrical connection in a direct manner or anindirect manner. Therefore, the description of “a first deviceelectrically connected or coupled to a second device” is to mean thatthe first device is connected to the second device directly or by meansof connecting through other devices or methods in an indirect manner.

Please refer to FIG. 1, which illustrates a schematic diagram of acomputer system 10 according to an embodiment of the invention. Thecomputer system 10 comprises a central processing unit 100, a storagedevice 102 and a user interface 104. Certainly, the computer system 10is not limited to comprising the above-mentionedelements/modules/circuits only, i.e. the computer system 10 may furthercomprises the motherboard, the memory, the hard disk (HD), the southbridge module, the north bridge module, the display panel, etc. In theembodiment, the central processing unit 100 may refer to any form ofelectronical device including, but not limited to, commodity CPU andGPU, which can execute instructions for realizing the indexing,relevance calculating, and other functionalities required in theembodiment. Moreover, multiple central processing units could be tightlyand/or loosely coupled with each other. The central processing unit 100is coupled to the storage device 102. Likewise, the storage device 102may refer to any form of device including, but not limited to, magneticdisk, RAID, solid state storage, optical storage, which can accommodateprogram codes (instructions), users' input data, intermediate operationresults, data base, and any other contents required in the embodiment.Similarly, multiple storage devices could be tightly and/or looselycoupled with each other. Also, the storage module 102 stores aprogramming code PC that is eligible to instruct the central processingunit 100 for processing an index method as well as a search method. Theuser interface 104 can be realized as a keyboard, a mouse, a joystick, atouch/display device, a mobile device or any electronic device via awired/wireless transmission with the central processing unit 100 forproviding electronic input signals, such that users can utilize the userinterface 104 to create, edit, collect and share the contents of theirmental models. Also, the central processing unit 100, the storage module102 and the user interface 104 could be connected with each other intightly-coupled (single site) or loosely-coupled (distributed) style,which is not limiting the scope of the invention.

Specifically, the computer system 10 is utilized to process a pluralityof structures which are derived from a plurality of externalizations ofusers' mental models. The plurality of externalizations of users' mentalmodel are obtained via a mind map, a concept map, a knowledge map, adiagram or a category, which means that the plurality ofexternalizations of users' mental model can be regarded as anestablished mental schema or cognition (i.e. pre-conceived ideas inparticular schemas) for interpreting the users' understandings ofcertain search targets as an object in cognition. Also, each of theplurality of structures derived from the plurality of externalizationsof the users' mental models comprises a plurality of elements and aplurality of relations thereof, wherein each of the plurality ofelements is obtained via a text, an image, a sound, a video or anysymbols representing a user's conception, idea or mental content, andeach of the plurality of relations is obtained as a hierarchy, asequence order, a logical dependency or any specified state of affairsamong the plurality of elements, which is not limiting the scope of theinvention.

The storage device 102 of the embodiment may store/prepare with apredetermined principle of normalization as a programming code toimplement a process of normalizing structures in the form of tuple. Theprinciple of normalization comprise a segmentation information accordingto a length of capacity limits of human cognition, such as the length ofmemory span, and the embodiment of the invention may predetermine, butnot limited to, the length of capacity limits as a number of 4, 5, 7 or9. Besides, the storage device 102 of the embodiment may alsostore/prepare with a plurality of predetermined principles of relevancyas another programming code to implement at least one or more principlesof similarity calculation for the plurality of structures. Both theprogramming codes of the predetermined principle of normalization aswell as the plurality of predetermined principles of relevancy may beoperated to be cooperated with the programming code PC for processingthe index method as well as the search method, which is also in thescope of the invention.

In the embodiment, the index method, compiled as the programming codePC, can be directly summarized as an index process 20, as shown in FIG.2. The index process 20 comprises, but not limited to, the followingsteps:

Step 200: Start.

Step 202: Receive at least one of the plurality of structures.

Step 204: Analyze the structure according to the predetermined principleof normalization to obtain a plurality of index analysis results in aform of a plurality of tuples.

Step 206: Obtain the index store according to the index analysis result.

Step 208: End.

In step 202, the computer system 10 utilizes the user interface 104 toreceive the at least one of the plurality of structures. Also, a localarea network (LAN) or a wide area network (WAN) can be cooperated withthe computer system 10, such that other computer systems or users canshare/interchange the plurality of structures with/through a pluralityof the computer system 10 of the embodiment, which is also in the scopeof the invention.

In step 204, the computer system 10 utilizes the processing unit 100 toanalyze the structure according to the predetermined principle ofnormalization, so as to obtain the plurality of index analysis resultsin the form of the plurality of tuples, wherein the tuples of theembodiment comprises the plurality of elements and/or the plurality ofrelations thereof related to the plurality of structures. Suppose thereis a structure structure_(—)01:{g, b, f, A, H, c, j, e, i, d}, in oneinterpretation, the element may be the appeared alphabet, and therelation is the order in their appearance, then the normalizedrepresentation of structure_(—)01 is to be the tuple of (g, b, f, A, H,c, j, e, i, d). In another interpretation, the element of the structurestructure_(—)01 may be the lowercase letter, and the relation isinterpreted as the alphabetic serial order, then the normalizedrepresentation of structure_(—)01 may be the tuple of (b, c, d, e, f, g,i, j); the tuple for the second interpretation can also be formulated asthe tuple of (j, i, g, f, e, d, c, b), the reversed one, as long as thedesigned schema can meet the requirement for the specifiedinterpretation. In the embodiment, the principle of normalization, as aninterpretation of specification, can vary with the specifications fordifferent discourses of applications. Such variety may be illustratedwith several embodiments later in following paragraphs.

Additionally, it is rational to exclude that the analysis of longstructure may meet the requirement of meaningful results as well ascomputation efficiency. Based on that consideration, the system parsesthe tuple of the original structure into finite index process units inthe form of tuples, i.e. the index analysis results, by segmenting withevery certain number of consecutive nodes according to the segmentationinformation while performing indexing operations. In one embodiment, ifthe segmentation information is a number of 7, then structure_(—)01 isindexed with the index process units of (a, b, c, d, e, f, g), (b, c, d,e, f, g, h), (c, d, e, f, g, h, i), (d, e, f, g, h, i, j). In otherwords, the structure is indexed according to its index analysis results.

In step 206, the computer system 10 utilizes the processing unit 100 andthe storage device 102 to store the index analysis result for furtheroperations, so as to obtain the index store, which can also be stored inthe computer system 10. What should be stressed, the index schema forthe invention can be open for the system designs in need. Theestablishment of the index store of the embodiment can be implementedwith various techniques known in the art. In one embodiment, theplurality of structures can be indexed with each of the tokensrepresenting the elements of tuples. In another embodiment, theplurality of structures can be indexed with the string sequencerepresenting the tuple. The operations of obtaining index may beexplained with two embodiments as followed.

First, for a common discourse of the two embodiments, let the documents,be the retrieved structures normalized in the form of tuples; supposethe three documents in handled are

-   -   doc_(—)01=(A, X, B, Y, C, Z);    -   doc_(—)02=(C, Z, B, Y, X);    -   doc_(—)03=(A, B, Z, T).

Please refer to FIG. 6, which illustrates a schematic diagram of anindex schematic table 60 for the embodiment of indexing with elements.As shown in FIG. 6, the index schematic table 60 comprises sevenelements A, B, C, X, Y, Z, T and three documents doc_(—)01, doc_(—)02and doc_(—)03. The index schema 60 of the invention can be furtherpredetermined with the programming codes stored in the computer system10, and the search process 30 can be adaptively operated to identify thetuples comprising all the elements of at least one of the tuples ofsearch analysis results and compute the similarity between the sequenceof the identified tuple and the sequence of the tuple of the querytarget structure according to the principles of similarity predeterminedas required. Notice again, the structure is indexed with its indexanalysis results. For example, in one embodiment, the segmentationinformation is a number of 3, then doc_(—)01 may not be identified by atarget tuple of (A, B, C) because the analyzed index process units ofdoc_(—)01 are (A, X, B), (X, B, Y), (B, Y, C), and (Y, C, Z).

Also, please refer to FIG. 7, which illustrates another schematicdiagram of an index schematic table 70 for an embodiment of indexingwith the string sequences representing the tuples. As shown in FIG. 7,the index schematic table 70 comprises the hidden structures and thethree documents doc_(—)01, doc_(—)02 and doc_(—)03. Initially, thesystems will analyze all the subsequences, as the hidden structures ofthe structure. Suppose the document is schematically defined as (α, β,γ), then the hidden structures of the document analyzed, in oneprototypical embodiment, is to be represented in the sequences of

-   -   (α, β, γ);    -   (α, β,);    -   (β, γ);    -   (α, γ);    -   (α);    -   (β);    -   (γ).

Any two of documents having a same hidden structure share a same key ofthe index. For example, doc_(—)01 and doc_(—)03 share the key of (A, B)because all of them have the hidden structure of (A, B). Likewise,doc_(—)01 and doc_(—)02 may further share the key of (B, Y) because theyalso have the hidden structure of (B, Y), but not for doc_(—)03. Inpractice, if a key of index does not exist, the system will create it;if existing, the system updates it with new documents. Accordingly, theindex schema 70 of the invention may be also stored/prepared in thecomputer system 10, as well as the index store obtained. And pleasenotice that again, the operation of analyzing hidden structures is onlyapplied to the index process units of the structure, and thus the systemestablishes the index of the structure. The same example for doc_(—)01with segmentation information of number 3 can also be the illustrationhere. The difference between the two embodiments is just the design wayof index schema; one is done with (Intersection of) the elements, andthe other is done with the sequences.

Noticeably, the above mentioned two embodiments of index schema can alsobe correlated with the raw data of original structures that are indexedwith the tuples, in the way of, but not limited to, adding column (s) oraccessing other module (s) storing the raw data, so that the system canrefer to the original data for further utilization. Other required dataare also eligible for the integration of the present embodiments, whichis also in the scope of the invention.

Furthermore, during processing the index process 20, other paralleloperations as receiving corresponding relevant data and establishingreference data store can be performed. Corresponding relevant data maybe of all the data managed along with/for the mental model, such as, butnot limited to, the data grouped under or defined with the structure,the note for edition, or user information. More examples can beillustrated in the following paragraphs.

Further, the search method, also compiled as the programming code PC,can be directly summarized as a search process 30, as shown in FIG. 3.The search process 30 comprises, but not limited to, the followingsteps:

Step 300: Start.

Step 302: Receive at least one search query identifying one of theplurality of structures.

Step 304: Analyze the structure according to the predetermined principleof normalization, to obtain a plurality of search analysis results in aform of a plurality of tuples.

Step 306: Process an identification search process to identify, in anindex store, a plurality of structures comprising at least one of theplurality of tuples.

Step 308: Perform a calculation operation for a plurality of identifiedstructures according to predetermined principles of relevancy, so as toobtain a plurality of relevancy analysis results.

Step 310: Rank the plurality of identified structures according to theplurality of relevancy analysis results, so as to obtain a searchreport.

Step 312: Output the search report to a user's terminal.

Step 314: End.

In step 302, the computer system 10 utilizes the user interface 104 toreceive at least one search query identifying one of the plurality ofstructures, and operations of step 302 can also be understood throughoperations of step 202 of the index process 20, so as toshare/interchange the search query identifying one of the plurality ofstructures with other computer systems through the LAN and/or WAN, whichis also in the scope of the invention.

In step 304, being aligned to step 204, the computer system 10 utilizesthe processing unit 100 to analyze the structure according to thepredetermined principle of normalization, so as to obtain the pluralityof search analysis results in the form of the plurality of tuples. Also,the tuples of the embodiment comprises the plurality of elements and/orthe plurality of relations thereof related to the plurality ofstructures. In addition, the system will reformulate the tuple ofreceived structure into more tuples by permutation of elements, so as tomake the query expanded.

In step 306, the computer system 10 utilizes the processing unit 100 toprocess the identification search process to identify the structurescomprising at least one of the tuple of the search analysis via theindex store, so as to obtain the plurality of identified structures.Besides, the identification search process also comprises otheroperation such as accessing the reference data store of thecorresponding relevant data associated with the plurality of identifiedstructures, and preparing the accessed reference data for furtherutilization.

In step 308, the computer system 10 utilizes the processing unit 100 toperform the calculation operation for the plurality of identifiedstructures according to the predetermined principles of relevancy, so asto obtain the plurality of relevancy analysis results. In theembodiment, the predetermined principles of relevancy comprise at leastone or more principles of similarity calculation for the plurality ofstructures. In detail, the tuples of the embodiment can be utilized as anormalized representation for the plurality of structures. In that, thecalculation of structural similarity can be applied to suchrepresentations to measure and rank the plurality of structuresaccording to the similarity of the tuples, i.e. the normalizedrepresentative sequences. The calculation of structural similarity forthe tuples may be implemented, but not limited to, with the applicationof common techniques, such as Longest Common Subsequence (LCS), VectorSpace Model (VSM), Edit Distance (ED), Structural Pattern Recognition,any combination of the above or other proposed techniques.

For example, suppose the analyzed tuples of received two query targetsare QT_(—)01=(A, B, C) and QT_(—)02=(B, Z), and the tuples in handledremain doc_(—)01: (A, X, B, Y, C, Z), doc_(—)02: (C, Z, B, Y, X) anddoc_(—)03: (A, B, Z, T). In one embodiment of LCS, if the user inputsthe query target as for the query target QT_(—)01: (A, B, C), thedocuments doc_(—)01, doc_(—)02 and doc_(—)03 have corresponding valuesas doc_(—)01_LCS=(A, B, C), doc_(—)02_LCS=(B) and doc_(—)03_LCS=(A, B),respectively, and then ranking values of relevancy analysis can beobtained as doc_(—)01_rank=1, doc_(—)02_rank=3, and doc_(—)03_rank=2. Inone embodiment of ED, if the user inputs the query target as for thequery target QT_(—)02:(B, Z), the documents doc_(—)01, doc_(—)02 anddoc_(—)03 have corresponding values as doc_(—)01_ED=4, doc_(—)02_ED=5and doc_(—)03_ED=2, respectively, and then ranking values can beobtained as doc_(—)01_rank=2, doc_(—)02_rank=3, and doc_(—)03_rank=1.

In step 310, the computer system 10 utilizes the processing unit 100 torank the plurality of identified structures according to the pluralityof relevancy analysis results, so as to obtain the search report. Indetail, the search report comprises a list of the plurality ofidentified structures in a rank of relevancy analysis results and/or thecorresponding relevant data associated with the plurality of identifiedstructures accordingly.

In step 312, the computer system 10 utilizes the processing unit 100 tooutput the search report to the user's terminal, such as the displaypanel coupled to the computer system 10, which is not limited in thescope of the invention.

In brief, with the prepared index store, the search process 30 isoperated to analyze the inputted search query, so as to obtain theplurality of search analysis results in the form of the plurality oftuples, and accordingly, the identification search process as well asthe calculation operation can be operated to obtain the plurality ofrelevancy analysis results, so as to rank the plurality of identifiedstructures and correspondingly output the search report for the user(s). Accordingly, the embodiment of the invention utilizes thestructural and/or structure-like information and/or the information ofthe structure that is derived from user's mental model, rather thansplit and individual tokens of words or phrase retrieved from thedocuments, as an index unit and query for retrieving relevant documents,so as to provide another innovative approach for indexing and searchingthe plurality of structures. More practical embodiments of the inventioncan be demonstrated hereinafter as different specification and thenormalization of structures.

Hereinafter, several practical embodiments of the invention areintroduced. First, one embodiment of the invention specifies theinterpretation of specification and the normalization of structures asfor the discourse of classifications and/or categorizations. Thestructures can be interpreted as the hierarchies of classificationsand/or categorizations. In detail, the plurality of elements can berealized as word, images, voices, audios or any symbols representingusers' expressions, and the plurality of relations can be realized ashierarchical denomination of classifications and/or categorizations.Please refer to FIG. 4, which illustrates a schematic diagram of ageneral categorization 40 according to an embodiment of the invention.As shown in FIG. 4, the tuple 40 can be a general categorization GC. TheGC 40 may be first classified into two classifications CL_(—)1 andCL_(—)2. Next, the classification CL_(—)1 are further classified intotwo branch classifications CL_(—)1-1 and CL_(—)1-2, wherein theclassification CL_(—)1-1 comprises a classification CL_(—)1-1-1, and theclassification CL_(—)1-2 comprises two classifications CL_(—)1-2-1 andCL_(—)1-2-2. Also, the classification CL_(—)2 comprises a classificationCL_(—)2-1. Accordingly, the structures obtained from the GC maycomprises, in one interpretation, at least four categories as described,and the plurality of elements and the plurality of relations are theclassifications and their corresponding hierarchical relations. In that,the structures defined in terms of the plurality of elements and theplurality of relations thereof of tuple GC 40 are obtained to be atleast four categories, which can be analyzed in the form of tuples as

-   -   category_(—)01=(classification CL_(—)1, classification        CL_(—)1-1, classification CL_(—)1-1-1);    -   category_(—)02=(classification CL_(—)1, classification        CL_(—)1-2, classification CL_(—)1-2-1);    -   category_(—)03=(classification CL_(—)1, classification        CL_(—)1-2, classification CL_(—)1-2-2);    -   category_(—)04=(classification CL_(—)2, classification        CL_(—)2-1).

Certainly, the other categorizations of the invention can be realizedwith different classifications/categories, which is not limited thescope of the invention. Accordingly, the search query in the presentembodiment may be a category of user's intend, which may also bepresented, but not limited to, in the form of a sequence ofclassifications representing the hierarchy of the category. Once theuser inputs the search query, the search report in the form ofidentified categories after ranking operation and the relevant datathereof will be provided, wherein the relevant data can be realized asuser information, and collections grouped under categories such ashyperlinks, files, texts, sounds, videos, or images.

Moreover, another embodiment of the invention specifies theinterpretation of specification and the normalization of structures asfor the discourse of mind maps, concept maps or knowledge maps. Thestructures can be interpreted as the conceptual paths. In detail, theelements can be realized as the nodes, and the relations can be realizedas correlations of the nodes. Please refer to FIG. 5, which illustratesa schematic diagram of a mind map 50 according to an embodiment of theinvention. As shown in FIG. 5, the mind map 50 in the embodiment of theinvention comprises six nodes node_(—)1˜node_(—)6 with presenting atleast four conceptual paths. As shown, one is the path from root tonode_(—)1 and then to node_(—)2; another is from root to node_(—)1, andthen to node_(—)6; another is from root to node_(—)4, and then through acorrelation named relation_(—)1 to node_(—)5; and the other is simplyfrom root to node_(—)3. Let the nodes be the elements, and a correlationwith particular annotation also be seen as an element, the fourconceptual paths can be analyzed in the form of tuples, such as

-   -   path_(—)01=(root, node_(—)1, node_(—)2);    -   path_(—)02=(root, node_(—)1, node_(—)6);    -   path_(—)03=(root, node_(—)4, relation_(—)1, node_(—)5);    -   path_(—)04=(root, node_(—)3).

Certainly, the other mind maps of the invention can be realized withdifferent nodes and relations, which is not limiting the scope of theinvention. Accordingly, the search query in the present embodiment maybe a conceptual path of user's intend, which may also be presented, butnot limited to, in the form of a sequence of concepts. Once the userinputs the search query, the search report in the form of identifiedconceptual paths after ranking operation and the relevant data thereofwill be provided, wherein the relevant data can be realized as theinformation of the map, the author, annotations of edition or otherreferences.

Additionally, another embodiment of the invention specifies theinterpretation of specification and the normalization of structures asfor the discourse of diagrams or flows. The structure is interpreted aseach process of the flow. In detail, the plurality of elements can berealized as inputs, actions, conditions, and/or outputs of the flows,and the plurality of relations can be realized as logical dependency ofthe inputs, the actions, the conditions, and the outputs of the flows.Also, the logical dependency can be marked with different annotationssuch as transitive, recursive, symmetric and/or asymmetric, so that thenormalization can be defined as required designs. Processes of the flowsmay further comprise sub processes and so to be illustrated as differentdesigns/levels of the flows. In one embodiment of the generic view, thetuple can be realized as

-   -   flow_(—)01=(state_(—)01, state_(—)02, . . . , state_n).

Accordingly, the search query in the present embodiment may be a processof user's intend, which may also be presented, but not limited to, inthe form of a sequence of specified states. Once the user inputs thesearch query, the search report in the form of identified processes inthe rank of data relevancy and the relevant data thereof will beprovided, wherein the relevant data can be realized as actors, taskowners, service providers, demanded resources (i.e. expenditures,labors, transportation, etc.) and/or physical indexes (i.e. time ofprocess, temperature, etc.).

Further, another embodiment of the invention specifies theinterpretation of specification and the normalization of structures asfor the discourse of charts. The structure is interpreted as thetendency of indexes. In detail, the plurality of elements can berealized as tokens of one index value in the tendency, and the pluralityof relations can be realized as locations of tokens in the specifieddimension. Noticeably, measurement units corresponding to differentcharts can be easily transformed for different alignments, such that thelocations of the tokens among different charts can be directly utilizedto represent serial orders of the plurality of elements of the pluralityof tuples. For example, the tuple of the tendency of an index, in onegeneric embodiment, can be realized as

-   -   index_(—)01_tendency=(value_token_(—)01, value_token_(—)02,        value_token_(—)03 . . . ).

Under such circumstances, the search query in the present embodiment maybe an index of user's intend, which may also be presented, but notlimited to, in the form of a pattern of specified factors anddimensions. Once the user inputs the search query, the search report inthe form of identified converges of index tendency after rankingoperation and the relevant data thereof will be provided. The relevantdata can be realized as names of indexes/products/markets related todifferent timings and/or relevant events, and certainly, the charts ofthe embodiment should not be limited to comprise the X-Y coordinatechart, X-Y-Z coordinate chart, and/or any graphic/pie chart/table/barwith easy transformation of measurement units.

Notice that structures sharing a common key of the index may be seen asisomorphic. In the group of isomorphism, the systems can rank, inadvance, the relevancy of every single document and store the value withthe column “ranking”, according to the similarity between the sequenceof the documents and the sequence of the index key, i.e. the indexschematic table 80 with ranking as shown in FIG. 8. Suppose the twodocuments in handled are doc_(—)04=(A, Z, Y, B, X, C) and doc_(—)05=(A,B, Z, C, Y, X). Under one of prototypical definitions, let symbol (n)denote the sequential position of the element, the key (A, B, C) isdenoted as (A(1), B(2), C(3)), doc_(—)04 as (A(1), Z(2), Y(3), B(4),X(5), C(6)), and doc_(—)05 as (A(1), B(2), Z(3), C(4), Y(5), X(6)).Comparing to the key (A, B, C), in one embodiment of VSM, doc_(—)05 mayobtain better similarity than doc_(—)04 because the hidden structure ofdoc_(—)05 that shares the key (A, B, C) is (A(1), B(2), C(4)) where thatof doc_(—)4 is (A(1), B(4), C(6)). Likewise, comparing to the key (Z, Y,X), doc_(—)04 may obtain a better similarity than doc_(—)05 because thehidden structure of doc_(—)04 that share the key (Z, Y, X) is (Z(2),Y(3), X(5)) where that of doc_(—)5 is (Z(3), Y(5), X(6)). In that, thesystems can do sorting before query requesting since the relevancycalculation can be conducted while indexing. The processes for bettercomputation efficiency described above are also in the scope of theinvention.

Noticeably, all the mentioned embodiments can also be adaptivelyadjusted/modified/changed/transformed to fit any other commonimplementation for cooperation/integration together, such that the rulesof normalization can be realized for both indexing and searching in oneof the embodiments. Thus, the programming codes of the index process 20and the search process 30 can be directly compiled into one or moreprogramming code (s), such that the computer system 10 of the inventioncan conveniently process the programming code(s) for indexing andsearching the plurality of structures, so as to provide the users thesearch report corresponding to the inputted search queries and thecorresponding relevant data. Certainly, those skilled in the art canobtain the search report in the form as images, audios, voices, or anycombinations of electronic files, which is not limiting the scope of theinvention.

Particularly, the embodiment of the invention can also be utilized as aneffective means of advertising with the essence of cognitive patternrecognition. Thus, the cognitive pattern recognition can inherit thesimilar predetermined principle of normalization and data relevancy asmentioned above by identifying similarity between the plurality oftuples and the plurality of structures. In practice, any two ofindividuals share a same (or similar) set of categories may very likelyhave many interests in common. For example, for two individuals havingthe categories such as “professional sports>USA>NBA” and “professionalsports>USA>NFL” respectively for their collection of information,plausibly they may also be interested in daily message of professionalsports, but not necessarily both interested in a new product of genuineleather basketball. In another case, for two that share “professionalsports>USA>NBA”, if one has another like “travel>overseas>Asia”, he maybe much more probably to purchase a ticket for NBA opening game atShanghai than the other whose category for travels is defined as“travel>camping>the Great Lakes”.

The utilization of advertisement can also be achieved with the systemsand methods of the invention explained above. In the embodiment, thestructures in the index store are the target structures and the relevantdata are the digital content, which are both predetermined for therequirements of advertisement. The received structure, as a searchrequest to the system, may be of any request content, such as, but notlimited to, an inputted user query, or the contents of categories, mindmaps dumped in web page, etc. If the request structure matches thetarget structure, the digital content is provided in the response of therequest.

Also, the embodiment of the invention can be utilized for social networkgroups and/or network forums, such that users comprising the similarinterests and inclinations can be classified into the same sub-groups toshare contact information with each other, which is also in the scope ofthe invention.

In last, those skilled in the art should adaptively make combinations,modifications and/or alterations on the abovementioned embodiment. Theabovementioned steps of the index process 20 as well as the searchprocess 30 comprising suggested steps can be realized by means thatcould be a hardware, a firmware known as a combination of a hardwaredevice and computer instructions and data that reside as read-onlysoftware on the hardware device, or an electronic system. Examples ofhardware can include analog, digital and mixed circuits known asmicrocircuit, microchip, or silicon chip. Examples of the electronicsystem can include a system on chip (SOC), system in package (SiP), acomputer on module (COM), or any mobile communication devices, which isalso in the scope of the invention.

In conclusion, the embodiment of the invention provides a method and acomputer system for indexing and searching a plurality of structuresthat is derived from a plurality of externalizations of users' mentalmodels. Based on an index store prepared with the predeterminedprinciple of normalization, the inputted search queries can beidentified, and further be measured with the predetermined principle ofrelevancy, so as to obtain a search report complying with users'requirements. Also, during the identification, the index store and thereference data store can also be updated to store relevantdata/documents. In that, users comprising diverse background knowledgeand different interpretations can adaptively obtain corresponding searchreport according to her/his individual ontologies or categorizations,and more efficient improvements of the computer system can beanticipated accordingly.

Those skilled in the art will readily observe that numerousmodifications and alterations of the device and method may be made whileretaining the teachings of the invention. Accordingly, the abovedisclosure should be construed as limited only by the metes and boundsof the appended claims.

What is claimed is:
 1. A method for indexing a plurality of structures,which are derived from a plurality of externalizations of users' mentalmodels, the method comprising: receiving at least one of the pluralityof structures; analyzing the at least one structure according to apredetermined principle of normalization to obtain a plurality of indexanalysis results in a form of a plurality of tuples comprising aplurality of elements and/or a plurality of relations thereof related tothe plurality of structures; and generating an index store according tothe index analysis result; wherein the plurality of externalizations ofusers' mental models are obtained via a mind map, a concept map, aknowledge map, a diagram, a flow, a chart or a category; wherein each ofthe plurality of externalizations of users' mental models is anestablished mental schema or cognition for interpreting users'understandings of certain search targets in a form of externalizedelements and externalized relations thereof, and each of theexternalized relations indicates each externalized sequence from one ofthe externalized elements to another one of the externalized elements;wherein each of the plurality of structures derived from a correspondingone of the plurality of externalizations of users' mental modelscomprises a plurality of elements and a plurality of relations thereof,each of the plurality of elements is obtained via a text, an image, asound, a video or any symbols representing a user's concept, conception,idea or other mental contents, and each of the plurality of relations isobtained as a hierarchy, a sequential order, a logical dependency orother specified states of affairs among the plurality of elements andindicates each sequence from one of the plurality of elements to anotherone of the plurality of elements.
 2. The method of claim 1, furthercomprising: receiving corresponding relevant data associated with theplurality of structures and establishing a reference data store for thecorresponding relevant data.
 3. The method of claim 1, wherein thepredetermined principle of normalization comprises a segmentationinformation representing a particular number indicating a length ofmemory span.
 4. A computer system for indexing a plurality ofstructures, which are derived from a plurality of externalizations ofusers' mental models, the computer system comprising: a centralprocessing unit; a user interface coupled to the central processingunit; and a storage device coupled to the central processing unit forstoring a programming code, and the programming code is utilized toinstruct the central processing unit for processing a method comprising:receiving at least one of the plurality of structures via the userinterface; analyzing the at least one structure according to apredetermined principle of normalization to obtain a plurality of indexanalysis results in a form of a plurality of tuples comprising aplurality of elements and/or a plurality of relations thereof related tothe plurality of structures; and generating an index store according tothe index analysis result; wherein the plurality of externalizations ofusers' mental models are obtained via a mind map, a concept map, aknowledge map, a diagram, a flow, a chart or a category; wherein each ofthe plurality of externalizations of users' mental models is anestablished mental schema or cognition for interpreting users'understandings of certain search targets in a form of externalizedelements and externalized relations thereof, and each of theexternalized relations indicates each externalized sequence from one ofthe externalized elements to another one of the externalized elements;wherein each of the plurality of structures derived from a correspondingone of the plurality of externalizations of users' mental modelscomprises a plurality of elements and a plurality of relations thereof,each of the plurality of elements is obtained via a text, an image, asound, a video or any symbols representing a user's concept, conception,idea or other mental contents, and each of the plurality of relations isobtained as a hierarchy, a sequential order, a logical dependency orother specified states of affairs among the plurality of elements andindicates each sequence from one of the plurality of elements to anotherone of the plurality of elements.
 5. The computer system of claim 4,wherein the method further comprising: receiving corresponding relevantdata associated with the plurality of structures and establishing areference data store for the corresponding relevant data.
 6. Thecomputer system of claim 4, wherein the predetermined principle ofnormalization comprises a segmentation information representing aparticular number indicating a length of memory span.
 7. The computersystem of claim 4, further comprising a user interface for users tocreate, edit, collect, or share users' mental models.
 8. A method forsearching a plurality of structures, which are derived from a pluralityof externalizations of users' mental models, the method comprising:receiving at least one search query identifying one of the plurality ofstructures; analyzing the at least one structure according to apredetermined principle of normalization, to obtain a plurality ofsearch analysis results in a form of a plurality of tuples comprising aplurality of elements and/or a plurality of relations thereof related tothe plurality of structures; processing an identification search processto identify, in an index store, a plurality of structures comprising atleast one of the plurality of tuples; performing a calculation operationfor a plurality of identified structures according to predeterminedprinciples of relevancy, so as to obtain a plurality of relevancyanalysis results; ranking the plurality of identified structuresaccording to the plurality of relevancy analysis results, to obtain asearch report; and outputting the search report to a user's terminal;wherein the predetermined principles of relevancy comprise at least oneor more principles of similarity calculation for the plurality ofstructures, and the plurality of externalizations of users' mentalmodels are obtained via a mind map, a concept map, a knowledge map, adiagram, a flow, a chart, or a category; wherein each of the pluralityof externalizations of users' mental models is an established mentalschema or cognition for interpreting users' understandings of certainsearch targets in a form of externalized elements and externalizedrelations thereof, and each of the externalized relations indicates eachexternalized sequence from one of the externalized elements to anotherone of the externalized elements; wherein each of the plurality ofstructures derived from a corresponding one of the plurality ofexternalizations of users' mental models comprises a plurality ofelements and a plurality of relations thereof, each of the plurality ofelements is obtained via a text, an image, a sound, a video or anysymbols representing a user's concept, conception, idea or other mentalcontents, and each of the plurality of relations is obtained as ahierarchy, a sequential order, a logical dependency or other specifiedstates of affairs among the plurality of elements and indicates eachsequence from one of the plurality of elements to another one of theplurality of elements.
 9. The method of claim 8, wherein theidentification search process further comprises accessing a referencedata store of corresponding relevant data associated with the pluralityof identified structures and preparing the accessed reference dataaccordingly for further utilization.
 10. The method of claim 8, whereinthe search report comprises a list of the plurality of identifiedstructures in a rank of relevancy analysis results and/or thecorresponding relevant data associated with the plurality of identifiedstructures accordingly.
 11. The method of claim 8, wherein thepredetermined principle of normalization comprises a segmentationinformation representing a particular number indicating a length ofmemory span.
 12. The method of claim 8, wherein the plurality ofrelations of the plurality of structures comprise a plurality of pathinformation to form a structural information, rather than split tokens,phrases or words, for the users to perform indexing and searching of thesearch query.
 13. A computer system for searching a plurality ofstructures, which are derived from a plurality of externalizations ofusers' mental models, the computer system comprising: a centralprocessing unit; a user interface coupled to the central processingunit; and a storage device coupled to the central processing unit forstoring a programming code, and the programming code is utilized toinstruct the central processing unit for processing a method comprising:receiving at least one search query identifying one of the plurality ofstructures via the user interface; analyzing the at least one structureaccording to a predetermined principle of normalization, to obtain aplurality of search analysis results in a form of a plurality of tuplescomprising a plurality of elements and/or a plurality of relationsthereof related to the plurality of structures; processing anidentification search process to identify, in an index store, aplurality of structures comprising at least one of the plurality oftuples; performing a calculation operation for a plurality of identifiedstructures according to predetermined principles of relevancy, so as toobtain a plurality of relevancy analysis results; ranking the pluralityof identified structures according to the plurality of relevancyanalysis results, to obtain a search report; and outputting the searchreport to a user's terminal via the user interface; wherein thepredetermined principles of relevancy comprise at least one or moreprinciples of similarity calculation for the plurality of structures,and the plurality of externalizations of users' mental models areobtained via a mind map, a concept map, a knowledge map, a diagram, aflow, a chart, or a category; wherein each of the plurality ofexternalizations of users' mental models is an established mental schemaor cognition for interpreting users' understandings of certain searchtargets in a form of externalized elements and externalized relationsthereof, and each of the externalized relations indicates eachexternalized sequence from one of the externalized elements to anotherone of the externalized elements; wherein each of the plurality ofstructures derived from a corresponding one of the plurality ofexternalizations of users' mental models comprises a plurality ofelements and a plurality of relations thereof, each of the plurality ofelements is obtained via a text, an image, a sound, a video or anysymbols representing a user's concept, conception, idea or other mentalcontents, and each of the plurality of relations is obtained as ahierarchy, a sequential order, a logical dependency or other specifiedstates of affairs among the plurality of elements and indicates eachsequence from one of the plurality of elements to another one of theplurality of elements.
 14. The computer system of claim 13, wherein theidentification search process further comprises accessing a referencedata store of corresponding relevant data associated with the pluralityof identified structures and preparing the accessed reference dataaccordingly for further utilization.
 15. The computer system of claim13, wherein the search report comprises a list of the plurality ofidentified structures in a rank of relevancy analysis results and/or thecorresponding relevant data associated with the plurality of identifiedstructures accordingly.
 16. The computer system of claim 13, furthercomprising a user interface for users to create, edit, collect, or shareusers' mental model.
 17. The computer system of claim 13, wherein thepredetermined principle of normalization comprises a segmentationinformation representing a particular number indicating a length ofmemory span.
 18. The computer system of claim 13, wherein the pluralityof relations of the plurality of structures comprise a plurality of pathinformation to form a structural information, rather than split tokens,phrases or words, for the users to perform indexing and searching of thesearch query.